Cash vs. Stock Deals: Bidders’ Performance in

Tech and Non-tech M&A

BACHELOR THESIS WITHIN: ECONOMICS NUMBER OF CREDITS: 15 ECTS  PROGRAMME OF STUDY: International Economics and Policy  AUTHOR: FEBI CAESARA WULANDARI, JI WANG  TUTOR: DOROTHEA SCHÄFER, ANDREAS STEPHAN  JÖNKÖPING  DECEMBER 2015

Evidence from Mergers and Acquisitions in Sweden

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Abstract. This paper researches the effects of choice of payment (cash and stock) and M&A type (technological and non-technological) on bidders’ performance. We investigate 500 events in Swedish market between 2005 and 2015. Moreover, we also control the size of firms and the value of takeovers. In this paper, we conduct an event study in order to generate abnormal returns for the bidders at and around the M&A announcement. This research generates statistically significant and positive abnormal returns for the bidders especially when deals are financed by shares. Moreover, we also find that the technological M&A brings about lower abnormal returns than non-technological M&A. When we control for payment choice in technological M&A, the result shows that technological M&A paid for in shares generates higher abnormal returns than technological M&A paid for in cash.

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Acknowledgement. The process of our thesis would have not gone so smoothly without the help and support from a number of people.

First of all, we would like to thank our supervisor Professor Dorothea Schäfer, for guiding and encouraging our ideas, for helping us organizing our thoughts, sorting out our confusions and being patient with us all the time.

We would also like to thank our co-supervisor Professor Andreas Stephan for providing us with the fundamental methodological basis and finance knowledge during our study. We are very grateful to Jönköping University for the courses offering that enrich our knowledge and broaden our minds. Last but not least, we want to thank our families and friends for their strong support and continuous encouragement. Overall, it was a great and unforgettable experience in our lives. We will keep going to pursue more achievements on the academic and career path in the future. Febi Caesara Wulandari & Ji Wang December, 2015

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Table of Contents 1   Introduction ................................................................................ 1  1.1   Research Problem ....................................................................................... 2  

2   Literature Reviews and Theories .............................................. 3  2.1   Introduction to Mergers and Acquisitions .................................................... 3  2.2   Motivations for Mergers and Acquisitions ................................................... 3  2.3   Event Study and Abnormal Return. ............................................................ 3  2.4   Payment Method and Performance ............................................................ 4  2.4.1   Efficient Market Hypothesis ..................................................................... 4  2.4.2   Overpayment Hypothesis ........................................................................ 4  2.4.3   Information Asymmetry Theory ................................................................ 5  2.4.4   Hubris Hypothesis .................................................................................... 5  2.4.5   Size Effect ................................................................................................ 5  2.5   Introduction of Technological M&A ............................................................. 6  2.5.1   Motives of Technological M&A ................................................................ 6  2.5.2   Short Term Value Creation in Technological M&A .................................. 7  2.6   Hypothesis .................................................................................................. 8  

3   Research Methodology ............................................................ 10  3.1   Data and Sample Description ................................................................... 10  3.2   Methodology ............................................................................................. 11  3.2.1   Deal Specific characteristics .................................................................. 13  3.3   Regressions .............................................................................................. 15  

4   Empirical Results and Discussions ....................................... 17  4.1   Bidders’ value creation: short-run market reaction ................................... 17  4.1.1   Bidders’ market reaction to acquisition announcement ......................... 17  4.1.2   Payment method and bidders’ performance .......................................... 18  4.1.3   Technological M&A and bidders’ performance ...................................... 19  4.1.4   Payment methods in technological M&A ............................................... 21  4.2   Multivariate Analyses and Discussions ..................................................... 22  

5   Conclusion ................................................................................ 25  6   References ................................................................................ 26  

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1 Introduction

The motives behind M&A are hard to comprehend. M&A activities have failed frequently as various research studies have shown that the rate of failures is not less than 50%. Bearing in mind these results, it is anticipated that many firms will evade M&A as much as they can. However, the actuality of M&A deals demonstrates the opposite outcome. In fact, M&A has grown continuously over the last 20 years. Based on previous studies, the characteristics of takeover are crucial in determining its process and outcome. In this study, we investigate a particular characteristic of M&A that is the choice of payment. When facing a currency choice, bidders have the options to choose either stock or cash deals in order to acquire targets. According to Faccio & Masulis (2004), it is very likely that cash deals require debt financing as many firms have constraints in liquid assets. Simultaneously, bidders who opt for cash payment have to consider the pros and cons of raising debts that may affect firms’ leverage, while bidders who choose stock finance may face corporate control threats. However, this paper focuses more on the importance of firms’ choice in making currency decision that either the acquisitions are paid in cash or stocks, rather than the financing choice. In the year of 2000, AOL acquired Time Warner for 164 billion dollars in stocks. Having considered the synergy that both companies would create, such as having a high-speed cable technology offered by Time Warner and extra 10 million subscribers resulted from the takeover, the future of the M&A seemed to be bright. Nevertheless, it turned out that the deal was considered as one of the biggest mistakes in corporate takeovers’ history. The acquisition led to a massive destruction of shareholders’ values. Market capitalization of AOL dropped from about 220 billion dollars to 20 billion dollars in 2002. On the other side of the coins, the tech goliath Google, announced its first significant takeover in 2014 via cash, Google filed an agreement to purchase Nest, a cutting edge thermostats and smoke detectors producer. Many reviewers were sceptical and disputing the benefits and drawbacks that Google would face out of acquiring Nest. In the same week following the announcement, Google’s stock increased by 3,3%. These two contrasting acquisitions trigger questions regarding the reasons behind companies’ over performance and underperformance after takeovers. Why was AOL in favour of stock payments? On the other hand why did Google opt for all cash payment? Does cash payment outperform stock payment in M&A activities?

The justification of M&A activities has always been revolving around synergy. It has been a holy grail for multinational companies around the world. Many academics come up with various interpretations of synergy. British researchers, Goold, M et al (1998), define synergy as a connector between businesses that will generate extra value. Nevertheless, the abnormal returns of stocks of post M&A are not positive according to previous researches (Dodd 1980; Asquith 1983; Hsu and Jang 2007). The high variance of abnormal returns in takeover can be explained by the characteristics of the bidders and targets. According to Majluf & Myers (1984) concerning information asymmetry theory, the choice of payment method in M&A reveals information of the market regarding bidders’ asset valuations. Based on the data from 1972 to 1981, Travlos (1987) conducts a research of payment methods using an event study, the research finds out that stock payment in acquisitions has brought much larger losses in comparison to cash payment. Many companies though are still in favour of stock payments. The previous studies regarding payment method of M&A show conflicting results. Dong et al. (2006) uses the sample period from 1964 to 1982 to investigate misevaluation of takeovers by identifying pre acquisition market valuation. This research finds that the stock payment brings about a positive 3, 86% of CAAR for the bidders. While cash payment generates a lower CAAR of a positive 0, 87%.

What other factors will explain the variation of abnormal returns in M&A? As it has been mentioned earlier, the variation of returns in M&A must be high due to the complexity of M&A characteristics. The recent wave in technological M&A triggers our curiosity to investigate this

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specific characteristic. Technological M&A, such as telecom, media, IT, pharmaceutical and so on have been driving the global M&A. For example, according to the Hi-Tech M&A Report by Mooreland Partners (2015), nine major Hi-Tech corporate buyers such as Google, Microsoft, Tripadvisor, Twitter and so on purchase at least one acquisition every month. Frequent acquisitions in High-Tech sector have become a sustainable growth and development strategy in technological M&A. The motivation behind technological M&A is to create a technological synergy through target firms’ commercialized technology (Puranam, Singh, & Zollo, 2006) and leveraging innovation (Ahuja & Katila, 2001). According to Zahra (2006) on the research of 12 new biotechnology companies in the United States, the research indicates that external technology acquisitions influence the overall company’s performance. Furthermore, it has a positive impact on sales growth and the net interest rate of the assets. As a result, the potential long run benefits of technological M&A may bring a value creation that influences the short-term abnormal return of firms. To support this argument, the finding from earlier research by Cannace & Man (2013) shows that the announcement of technological-motivated M&A resulted in a positive significant abnormal return. We will focus on Sweden as our geographical dimension. An annual M&A report written by KPMG (2011) shows that Sweden represents one third of M&A transaction in the Nordic area. Moreover, in the year of 2015, M&A activities in Sweden have been the largest number of deals so far among other Nordic countries. It consists of 80 deals that are worth 10,8 billion euros (Merger Market Group, 2015). Many tech companies in Sweden have their exits, and are acquired by bigger companies. A study by Faccio & Masulis (2005) shows that the involvement of equity financing in Nordic acquisitions (including Swedish M&A) is the highest among European countries. Moreover, Sweden represents for about 10% of the world’s billion dollar exits. Due to its large market, an extensive tech scene and a high involvement of equity finance in Swedish market, we find that Sweden is an ideal venue to be observed.

1.1 Research Problem Our main research problem to be investigated is; “How does the choice of payment influence the short- term value creation of the bidders in technological and non-technological M&A?

The goal of this research is to find out whether cash or stock payment can explain the variation of market’s short run reaction at and around the M&A announcement. In order to measure the market reaction, we apply event studies here and calculate cumulative abnormal return. Moreover, we would also like to investigate different implications that are generated by different payment methods in technological and non-technological M&A. We compare the abnormal returns that technological M&A generates with those in non-technological M&A in order to evaluate the effect of technological factor in takeovers. It will enable us to interlink managers’ perception on the choice of payment method, technological factors and market’s reaction. Furthermore, we would like to analyse and compare the consistency of previous empirical evidences with our finding, and whether previous empirical evidences hold or not under different circumstances.              

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2 Literature Reviews and Theories

2.1 Introduction to Mergers and Acquisitions Mergers and Acquisitions aim to increase shareholders value. The result of combined companies’ values is expected to be higher than the value of the company as a single entity. The terms of Mergers and Acquisitions have been perceived as synonymous. However, both terms have slightly different definitions. Acquisition takes place when a bidder buys another company that is considered as a target. By definition, acquisition happens when a bigger company purchases a smaller company. In reality, there are many cases in which the smaller companies acquire the management control of bigger companies. Post-acquisition, the stocks of the bidders continue to be listed on the stock market. On the other hand, targets’ stock is no longer traded. Moreover, a merger can be described as an event where two companies become one (Weston & Copeland, 1992). A famous example of merger is when Daimler-Benz merged with Chrysler. The two companies surrendered their original names and combined both names into a new name, Daimler-Chrysler. Furthermore, in a merger, new stock is issued under the new company name. In this paper, we treat both terms as having the same meaning.

2.2 Motivations for Mergers and Acquisitions As mergers and acquisitions are expected to generate value creation, synergy motives come into the picture. In order to realize value creation, the related synergy has to be bigger than the premium paid by the acquirers. According to Moeller, Schlingemann & Stulz (2005), the synergy gain also exists when bidders’ shareholders gain from takeovers or when the loss of bidders’ shareholders is less than the targets’ shareholders. However, synergy is seldom to create shareholders’ value according to Sirrower (1997). Generally, synergy can be classified as either operational synergy or financial synergy.

Operational synergy is associated with economies of scale and scope. According to Zhovtobryukh (2014), the combined firms may achieve economies of scale and scope through a reduction of operating costs such as cost in R&D, distribution, production, marketing and so on. The realization of synergy can also be achieved through acquiring intangible assets such as technology from target firms in takeover. As technology is incorporated in patents, other intangible assets also include trademark, goodwill, copyrights and so on. A thorough explanation regarding technological synergy will be elaborated under the technological M&A chapter.

Ravenscraft & Scherer (1987) identify several activities that determine the realization of economies of scope such as vertical integration, the knowledge transfers between bidders and targets, bringing together specific asset under common control to mitigate agency costs, and so on. Moreover, Operating synergy can be achieved mainly through merging in related companies or the same industries (Comment and Jarrell, 1995).

2.3 Event Study and Abnormal Return. Would we want to analyse the effect of company events such as IPO, earnings announcements, mergers and acquisitions, and many more on the value of the firm? In order to explore those questions, Event Study will be a useful tool in evaluating and understanding the short run momentum of mergers and acquisitions. It is widely known that economist and scholars use event studies to comprehend the effects of information on the behaviour of company’s stock in the marketplace. James Doyle (1993) executes the first event study using 95 samples listed in NYSE from 1921 to 1931, he analyses the effects of stock splits on price and concludes that 60% of the investigations leads to price increased (MacKinlays, 1997). Over time, event studies become more sophisticated. Fama et al. (1969) develops the event study into a more useful form. In order to analyse the effect of mergers and acquisitions on its value, researchers use abnormal returns. It can be defined as the difference between the real return after the event and the expected return of stock pre event. We will examine abnormal return further on the fourth chapter of this paper.

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2.4 Payment Method and Performance The choice of payment method in M&A plays a big role in determining the announcement’s return that the acquirers generate. According to various studies that focus on the acquisition of public listed targets (Travlos, 1987; Wansley, Lane, & Yang, 1987; Amihud et al., 1990, and Brown & Ryngaert, 1991), the acquirers’ average announcement returns for those who are using stock payment bring about a significantly negative result rather than those who are using a cash payment. In general, an acquirer will use a cash payment when the stock of its company is undervalued, and using a stock payment when the value is overestimated (Fuller et al., 2002). However, in technological M&A, researchers find dissimilar results. Researchers such as Kohers and Kohers (2000) use the high-tech data from 1987 to 1996 conveys that regardless the use of cash or shares in financing the acquisition, the announcement return in high technological acquisitions brings a significantly positive abnormal return. However, Cannace & Man (2013) find a negative relationship between cash financing and abnormal returns in acquisition’s announcement. There are various theories that explain the reasons behind the choice of payment method and its effects on companies’ stocks. Information and behavioural economics lay the foundation of the theories of choice of payment methods. Those theories are overpayment hypothesis, information asymmetry theory, hubris theory, and size effect. Moreover, before we are going to review these theories behind the choice of payment in M&A, we will start with efficient market hypothesis as the fundamental factor that determines the stock prices and market behaviour.

2.4.1 Efficient Market Hypothesis Economists, psychologist in behavioural finance and econometricians have been constantly researching the movement of price changes due to firms’ events, such as, stock splits, earnings announcements, mergers and acquisitions, IPO and so on. As a result of researchers’ observations on the stock behaviours of companies that participate in events, efficient market hypothesis comes to light. Fama, Fisher, Jensen, & Roll (1969) summarise that the market is efficient, as the stock price is rationally priced and quickly adjusted to all new information in the market. This result is based on the study of stock splits and its effects on the stock value. Moreover, Fama (1970) introduces three forms of efficient market hypothesis based on the nature of the information. Firstly, the weak form of efficient market hypothesis declares that historical prices and past information are reflected in stock price. Secondly, the semi strong form of efficient market hypothesis reveals that all publicly available information is incorporated in market price. Thirdly, the strong form of efficient market hypothesis avows that stock price rapidly reflects all privately and publicly available information. In summary, investors are not able to continuously gain an excess return. Efficient Market Hypothesis receives strong critics from many researchers in the field of behavioural economics and econometrics. Behavioural economists challenge the efficient market hypothesis and oppose the notion randomness in stock prices. The behaviourists claim that the short run momentum can be explained by “bandwagon effect”, which means the tendency of people to do something because of others doing the same. Other explanation for short run momentum is due to market under reaction to new information, while econometricians maintain the theory that stock prices are predictable. Despites the critics that challenge the hypothesis, Burton G. Malkiel (2003) concludes that financial markets are more efficient and less predictable than what oppositions claim.

2.4.2 Overpayment Hypothesis The study of the winners’ curse by Varaiya & Ferris (1987) reports that in a competitive bidding situation, the winner is very likely the one who overestimates the value of the targets the most. Overpayment hypothesis proves when the expected gains that come from acquiring targets are lower than the premiums that are paid by the acquiring companies, it may lead to a negative association between premiums and returns (Varaiya & Ferris, 1987; Sirower, 1997). Moreover, acquirers can mitigate the winners’ curses by financing the deals with cash. From acquirers’ perspective, cash financed deals generate a significant return of 2%, while equity financed deals bring a loss of 0, 9% according to Franks et al. (1988).

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Overpayment hypothesis shows that cash financing will bring higher premiums to the targets than stock payments due to some factors such as capital gains on taxes, competition and the popularity of financing takeovers with cash. It is very likely for targets to accept deals that offer highest premium and finance with cash. According to the research of means of payments in takeovers by Franks et al. (1988), cash financed acquisition will generate higher bid premiums. Moreover, Franks et al. (1988) shows that equity financed acquisitions will avoid the actualization of capital gains for targets’ shareholders. The immediate capital gains can only be achieved when targets accept the acquisitions financed with cash. Taxes in stock financed deals will be delayed until the shareholders sell the shares offered in takeovers. Furthermore, Shleifer & Vishny (1997) elaborate that the winners’ curse phenomenon can be a sign of agency problems, as bidders’ managers exploit the acquisitions to their own benefits without taking into account the profits derived from the acquisitions.

2.4.3 Information Asymmetry Theory This theoretical background is developed by Myers & Majluf (1984). Information asymmetry is classified as a part of signalling models. This model explains that the choice of payment method by bidders’ managers conveys valuable information about the true value of the firm to the market participants. Myers & Majluf (1984) elaborate the objective of information asymmetry, which assumes the bidders’ managers acting in the best interest of their (old) shareholders, and have more information regarding the value of the company. Furthermore, Jensen (1986) states that acquirers will likely to choose stock payment when the value of the company is overvalued, and opt for cash payment when the value of the firm is undervalued. When managers act in the best interest of their (0ld) shareholders and the company is overvalued, managers will opt for stock payment that allows sharing the risk of losses with the new (target) shareholders. Moreover, the disclosure of stock financed deals give a signal to the market participants that the negative outcome will take place. The study of the choice of exchange medium in M&A by Hansen (1987) conveys a bargaining model under asymmetric information. According to this paper, when bidders’ managers do not know the value of the targets better than the targets’ managers, the bidders will prefer to finance the deal with stock. Furthermore, The research by Fishman (1989) on his theoretical paper of pre-emptive bidding and the role of the medium of exchange in acquisitions justifies that cash payment will eliminate the competition among bidders, thus, cash payment will increase the probability of deal acceptance by targets. He also states that a stock payment offering has its advantage when there is an information asymmetry regarding the inherent value of the targets. Other recent study by Coru & Isakov (2000) confirms cash payment passes the signal to the market that the acquirers hold a high value, thus cash payment will alleviate the competition in tender offer. Similarly to Myers & Majluf (1984), the paper by Hansen (1987) concludes that stock payment is expected to have a non-positive payoff. The empirical evidence by Travlos (1987) supports the outperformance of cash payment over stock payment due to asymmetric information. The research shows that cash payment generates a positive abnormal return of 0,29% while stock payment results in a negative abnormal return of 0,69%.

2.4.4 Hubris Hypothesis Overconfidence of bidders’ manager is the reason behind hubris hypothesis. Managerial hubris is the situation when the company overvalues the synergetic value in takeovers. A study of hubris hypothesis of corporate takeovers by Roll (1986) explains why bidders’ managers are willing to pay a deal value above the current market price. When hubris hypothesis exists in takeover, synergetic value is not available to takeovers’ participants. Moreover, the hypothesis also explains that the loss in acquirers’ market value is counterbalanced by the gain in targets’ market value. Empirical studies in bidders’ managers’ overconfidence show that the irrational managers who pay high premium tend to use cash, while the usage of stock payment is negatively related with high premium (Malmendier & Tate, 2008; Ismail, 2011).

2.4.5 Size Effect The study by Moeller, Schlingemann & Sulz (2004) confirms that smaller acquirers are likely to earn higher positive abnormal returns than larger acquirers. However, as the gains that the smaller acquirers generate are usually lower than the loss that larger bidders make, the

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empirical evidence on Moeller et.al (2004) shows that in average bidders lose about $25.2 million on announcement. Furthermore, the study also shows that smaller bidders are likely to use cash rather than shares as a payment method in acquisitions, and they tend to generate higher positive abnormal returns than the larger bidders using cash in takeovers. This evidence is in line with researchers’ assumptions, as smaller bidders tend to act in the interest of the shareholders. Moreover, the lower abnormal returns that larger bidders generate can be explained by negative synergetic gains of larger bidders due to managerial hubris. An academic research by Asquith et al. (1983) conveys that the bidder’s size effect on return can be captured by the ratio of target’s market capitalization to bidders’ target market capitalization. As the relative ratio increases when the acquirers are smaller, the abnormal returns for the smaller acquirers also increase. This is consistent with the hypothesis by Moeller et al. (2004) regarding bidders’ size effect. Asquith et al. (1983) shows that abnormal return increases, as the relative size ratio increases. It implies a positive relationship between acquirers’ size and return. Another study by Travlos (1987) demonstrates a negative coefficient of relative size, which conveys a negative relationship between bidders’ size and return. There are various ways to measure relative size. Based on a research by Fuller et al. (2002), the relative size defines as the target market (deal) value divided by bidders’ market capitalisation. Moreover, other academic researches that focus on the target market (deal) value confirm there is a significantly positive relationship between transaction value and bidders’ return. This means, the higher relative size of target market (deal) value brings a higher bidders’ excess return (Benou and Madura, 2005). The following academic research is conducted in high-tech takeovers, it reports a positive relationship between targets’ size and bidders’ excess return. Taking over a larger target is expected to create a higher synergy in comparison to a smaller one (Kohers & Kohers, 2002).

2.5 Introduction of Technological M&A Technology sector has grown very fast for the last decade. According to Koh & Venkatranam (1991), the economic importance of technological sector has become prevalent and given rise to innovation-drive takeovers. By definition, technological acquisitions are involving absorption of technological inputs of target firms to the acquiring firm’s knowledge based (Ahuja & Katila, 2001). In result, the acquirers will expand its technological competitive advantage by increasing acquiring firms’ innovation output. The recent literature by Zhovtobryuh (2014) defines technological acquisition, as an acquisition that focuses on technology as the main assets that acquirers would like to control in the acquisition. Innovation-driven acquisitions of technological targets are considered to be faster and cheaper in comparison to developing the technological innovation internally (Rauft and Lond, 2000). Frequent acquisitions in technology sector have become the solution to sustainable growth for acquirers firms. Various quantitative researches propose that acquisition of technological companies receive positive market perception (Hansen, 1987; Travlos, 1987; Bradley, Desai, and Kim, 1988; Amihud, Lev, and Travlos, 1990; Brown and Ryngaert, 1991; and Servaes, 1991). However, a high enthusiasm by market participants in high-tech sector may become non-viable, and it may destroy the sustainable growth potential of technological acquisitions (Kohers & Kohers, 2001). Hi-tech operation characterizes by a complex technology that may cause a high uncertainty of hi-tech firms, and an error of market judgement (Kohers & Kohers, 2001). Several studies in long-term value creation of acquisitions show conflicting results. Some researchers find out that there is no significant abnormal return (Franks, Harris, and Titman, 1991), while other studies show that there is a positive long-term excess return. Moreover, the recent study of short-term momentum in technological M&A by Canace & Mann (2013) presents a significant and positive abnormal return. Under this section, we discuss more empirical evidences on short-term value creation in takeovers. We begin with discussing the motives of technological M&A as follows.

2.5.1 Motives of Technological M&A Previous literatures discuss that there are several motives behind technological M&A. Ahuja & Katila (2001) propose that technological input is the factor that differentiates technological

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acquisitions from non-technological ones. We discuss three reasons behind technological M&A that serve as technological synergy. According to some researchers, the first reason behind technological acquisitions is to gain from targets’ innovation. The transfer of targets’ innovation to firms’ knowledge base may enhance firms’ economics of scale and scope in firms’ R&D. An empirical evidence of technological M&A in telecommunication industry by Gantumur & Stephan (2011) shows that mergers and acquisitions significantly increase firms’ innovation performance. As acquisitions enhance economics of scope and scale in R&D, there is a positive relationship between innovation and productivity growth (Ortega-Argile and Potters, 2011). The second reason for firms to engage in technological acquisitions is to close the gap between targets’ and acquirers’ R&D activities. According to de Man & Duysters (2005), the advantage of technological M&A goes to both targets and acquirers, as acquisitions give the opportunity that both firms may not realize alone. This gives an opportunity for both firms to merge their technological knowledge and develop innovation in order to produce new products. From the targets’ perspective, technological acquisition may allow them to take advantage of acquirers’ financial resources to fund projects. The third reason is to gain from technological commercialization of target firms. A thesis by Zhovtobryuh (2014) elaborates that technological commercialization can be achieved through the combination of technological innovation of targets’ firms with complementary assets of acquirers. For instance, targets of technological M&A that belong to group of innovative start-up companies may gain benefits from acquisitions. This benefits include actualisation of technological commercialization, since innovative start-up companies are usually lacking complementary assets to manufacture, market and providing after sales service for the products (Granstrand & Sjolander, 1990; Teece, 1986). The study by Zhovtobryuh (2014) concludes that realisation of technological commercialization does not necessary require the involvement of acquirers to develop targets’ innovation, yet acquirers may provide complementary assets in order to profit from commercialisation, and help the targets to eliminate potential competitors.

2.5.2 Short Term Value Creation in Technological M&A Technological M&A promises a significant positive abnormal returns for the shareholders due to the long term benefits that it may create. Empirical evidences in technological M&A mostly report positive abnormal returns at and around announcement (Kohers & Kohers, 2002; Benou and Madura, 2005; Con et al, 2005; Higgins and Rodriguez, 2006; Kallunki, Pykkö & Laamanen, 2009; Dutta & Kumar, 2009; Canace & Mann, 2013). However, Sears & Hoetkers (2014) using evidence from the US samples prove a negative abnormal return for the technological M&A. The failure of high tech M&A has something to do with the high uncertainty nature in high-tech acquisitions. High-tech acquisitions are associated with higher degree of information asymmetry than non-tech acquisitions. The valuation of high tech targets is the main reason of uncertainty in technological M&A, as high tech targets own intangible assets and high growth benefits that are difficult to be valued (Canace & Mann, 2013). The characteristics of technological M&A control the bidders’ abnormal return. The study by Benou & Madura (2005) elaborates that the ownership structure of the target determines the variation of the abnormal return. Bidders of private targets generate a significant and positive abnormal return of 1.08%, while acquirers of public targets bring about a statistically significant and negative abnormal result of 2%. Furthermore, the study proves that cash finance is more favourable than stock payment in hi-tech acquisitions of private target, though it is widely known that stock payment acquisitions are preferable in acquisitions of private targets. Negative market reaction of stock payment due to overvaluation is prevalent in acquisitions in general. However, Empirical studies of short run momentum of technological M&A, including payment method as control variables, show mixed results. The study by Canace & Mann (2013) using US samples confirm that cash payment in technological motivated M&A is negatively associated with acquirers’ abnormal returns. Moreover, an empirical research by Kohers & Kohers (2000) reports that technological M&A whether it is financed by cash or stock generates a significantly positive abnormal return for US samples. On the other hand, several researches in technology-motivated acquisition show a consistent result with non-technological

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acquisitions regarding the use of stock financing in acquisition. Shares financing by R&D intensive acquirers tend to decrease acquirers’ value (Dutta & Kumar, 2009; Ang & Kohers, 2001; Finkelstein & Haleblian, 2002).

2.6 Hypothesis Based on the nature of information in a full assumption of efficient market under section 2.4.1, all new information (announcements) is incorporated and reflected in the stock price and the market as a whole rapidly and rationally. According to Burton G. Malkiel (2003), the term of financial market efficiency suggests that the investors are not able to earn an excess return. Hence, without accepting above-average risks, above-average returns do not exist. Moreover, mergers and acquisitions do not always create short-term shareholders value (Sirrower, 1997). There are some factors such as managerial hubris (chapter 2.4.4), lack of integration process in M&A, and so on that may destroy the positive expectation in creating short term shareholders values. Furthermore, other characteristics such as payment method and technological factors may also influence abnormal returns. Due to the reasons above, we expect that acquisitions do not automatically generate an excess return. As a baseline for our further hypotheses, the first hypothesis to be tested comes as follows: Hypothesis 1: Announcements of mergers and acquisitions are expected to increase bidders’ abnormal return at and around announcement. The choice of payment method is a crucial characteristic that determines the abnormal returns of bidders. From the previous sections, our theoretical frameworks regarding overpayment hypothesis under section 2.4.2, information asymmetry theory under section 2.4.3, and size effect under section 2.4.5 convey the preference of cash payment over stock payment. According to those theories in overall, cash deals generate higher abnormal returns than stock deals. Overpayment hypothesis states that financing acquisitions in cash can alleviate the winners’ curse situation. Cash payment generates 2% CAR, while shares payment makes -0,2% CAR (Franks et al., 1984). Furthermore, Majluf & Myers (1984) regarding information asymmetry postulate that the assets’ valuation of firms influence the choice of payment methods. Acquisitions financed with stock give negative signals to the market, while acquisitions paid for in cash provide positive signals to the market. According to Fuller et al. (2002), stock payments will be used in acquisitions when the companies are undervalued, and cash payments will be used when the firms are overvalued. Researchers such as Travlos, (1987), Wansley, Lane & Yang, (1987), Amihud et al. (1990) and Brown & Ryngaert (1991) confirm higher positive abnormal returns for acquirers who are using cash payment rather than those who are using stock payment. Moreover, the theory of size effect also postulates the preference of cash deals over shares deals by smaller bidders. The study of M&A payment method including the Swedish market is conducted by Faccio & Masulis (2005). In this research, they analyse 197 samples of Swedish acquirers altogether with other European samples. The empirical evidence shows the preference of cash payment over stock payment. This leads to our second hypothesis: Hypothesis 2: Mergers and Acquisitions financed in cash by bidders are more preferable than acquisitions financed in shares by bidders. The difference between technological and non-technological M&A is determined by the technological input from the target that is transferred to the acquiring firm’s knowledge base. Non-technological M&A though will not benefit from the technological input, while the technological M&A benefits from the economies of scope and scale in technological and innovation development as well as technological commercialization discussed under section 2.5.1 regarding “Motives of Technological M&A”. Moreover, as it has been discussed under section 2.5.2, the long-term benefits such as a sustainable high growth opportunity associated

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with technological acquisitions create a positive short-term value creation at and around announcements (Kohers & Kohers, 2002; Benou & Madura, 2005; Con et al, 2005; Higgins & Rodriguez, 2006; Kallunki, Pykkö & Laamanen, 2009; Dutta & Kumar, 2009; Canace & Mann, 2013). Based on the theoretical backgrounds and empirical evidences in technological M&A, it leads to our third hypothesis: Hypothesis 3: Abnormal returns of bidders in non-technological acquisitions at and around announcement are less than those of bidders in technological acquisitions. The uses of cash payment in deals tend to create positive market reaction. While, the uses of stock payment in deals tend to generate negative market reaction. The statement has been supported by various studies in M&A payment method discussed under section 2.4.2, 2.4.3, and 2.4.5. However, the studies in short term value creation in technological M&A that has been explored under section 2.5.2 point out conflicting results. Canace & Mann (2013) show that involvement of cash financing in technological M&A results in a negative abnormal return for US samples from 1995 to 2003. Other empirical research by Kohers & Kohers (2000) using US samples from 1987 to 1996 shows that technological M&A creates a positive abnormal return whether the deals financed in cash or shares. Our fourth hypothesis to be tested is as follows: Hypothesis 4: Technological acquisitions financed in shares by bidders are more preferable than technological acquisitions financed in cash by bidders.

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3 Research Methodology

3.1 Data and Sample Description The data analysed in this study is derived from the Zephyr on mergers and acquisitions database, which we use for Swedish technology as well as non-technology M&A deals from 2005 to 2015. Firstly, all of our transactions are filtered based on the following criteria: (i) the deals were announced or completed; (ii) deal types are mergers or acquisitions (iii) the acquirers are publicly-listed Swedish firms on the Nasdaq OMX Stockholm index, (iv) the deals were announced between 01/09/2005 and 01/09/2015, (v) the method of payments is either cash or stock, (vi) all transactions have deal value. In result, 542 deals satisfy the above-mentioned criterions. Secondly, to distinguish between technological and non-technological M&A, here we classify our sample as technological with three-digital SIC code that quoted from Kile and Phillips (2009) for high technology targets that are regarded as the acquired assets. The optimal 11 recommended code combination are: 283-drugs; 357-Computer and Office Equipment; 366 -Communication Equipment; 367-Electronic Components and Accessories; 382 -Laboratory, Optic, Measure, Control Instruments; 384-Surgical, Medical, Dental Instruments; 481-Telephone Communications; 482-Miscellaneous Communication Services; 489-Communication Services, NEC; 737-Computer Programming, Data Processing; 873-Research, Development, Testing Services. Thus Zephyr generates 211 observations for technological M&A that meet the above-mentioned requirements. The reason we select those high-tech sectors to be our technological M&A is due to the important motivation of technological M&A is to obtain the expected benefits for the acquirer via synergy effect (Chesbrough, 2003), particularly in high-tech industries, high-technology mergers generate innovation ability from external capital stock under technological M&A activity to supplement the existing technology assets (Higgins & Rodriguez, 2006). Meanwhile, for high-tech companies, the development of the technology capability mainly reflects in its patent, which is an important embodiment for the firm’s innovation performance after M&A (Hagedoorn & Cloodt, 2006). Thirdly, Ahuja (2001) proposes that the innovation of the enterprise performance is embodied in two aspects: The first aspect is R&D expense, and the other is the approved numbers of patents. Therefore, we restrict our sample that the target firm has at least 1 patent being registered before the announcement date. We extract the output from Zephyr and match the target BvD ID numbers to Amadeus database. There are 54 target firms meeting our requirement. Therefore, we define our technological M&A based on if the target firm either has a high-tech SIC code or has had patent activity preceding the M&A announcement, 215 meet the above-mentioned classification. Finally, according to the efficient market theory, the market could reflect the information quickly and effectively on the value of the company. In the efficient market, stock price reflects the company's internal operation and financial conditions. Our stocks data are applied on Thomson Reuters DataStream database. Several numbers of deals are excluded due to unavailable stock data on DataStream and overlapping bidders’ acquisition activity listing from Zephyr, which leaves us with 500 deals in total, 192 deals that are classified as technological M&A, and the rest of 308 deals that are classified as non-technological M&A.

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Figure 1. Swedish listed acquiring firms. Technological and non-technological distribution in the year of 2005-2015

From the numbers distribution point of technological and non-technological M&A, in the year 2007, technological deals accounts for the highest number that is 35 deals. The possible reason for the high M&A wave is due to Sweden has experienced a flourishing economy according to the data statistics by National Accounts (1993-2008). Thus, economic situation brings into correspondence with the Swedish M&A levels. However, by contrast, the most active year for non-technological transactions is in the year of 2011, which has reached to 40 deals. It appears that non-technology M&A plays a dominant role among Swedish acquiring firms. The outbreak of the global financial and economic crisis in 2008 has led to a low level of M&A deals, and continually keeping low in year 2009 under the global market uncertainty. Whereas, non-technological bidders are likely to recover faster within two years and increase until its highest level in 2011. Meanwhile, technological M&A starts to increase from 2014, but non-technological M&A decreases instead, which indicates the development of science and technology is promoting the rapid economic and social progress in today's world, more and more bidders prefer to obtain advanced technology, as the corporate strategy to cope with the changing market environment.

3.2 Methodology Our study uses MacKinlays(1997) event study methodology to analyse the specific impact from the event on the companies’ stock prices. This is a way to measure the change of shareholders value. Moreover, event study methodology explores if the event will cause the abnormal changes in the market that we define as the abnormal returns (AR) of the security price. We investigate whether it will generate AR at and around the event announcement. However, the announcement day of some specific events is uncertain. We find that several events have more than one announcement date. On this account, Fama & Blume (1966) develope the cumulative abnormal return (CAR) calculation method to add up all the abnormal returns during the event and to obtain the accumulative impact for the companies’ stock price. CAR illustrates the gains of the shareholders around M&A announcement. This is widely used to measure the expected M&A performance (Halebian & Finkelstein, 1999; Harford et al, 2012). We apply Brown & Warners (1985) Market Model of the event study. The model is a statistical model that interprets the stable linear relationship between the return of security and the return of the market portfolio. The merit of this model is to minimize the estimation error and the variance of the abnormal return by cutting out the part of the return that is related to the

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volatility in market returns. Moreover, it will be more beneficial for our study in order to detect the effects of the announcement. The following formula shows the calculation of the normal return of the security i on day t.

E(εit = 0) Var(εit) = σ εi

2

Rit is the security return i during the period t, Rmt is the market portfolio. αi, βi and σ εi2 are the parameters of the market model. εit is the zero mean disturbance term. The choice of event day is an important step in the event study methodology in order to observe the fluctuation of the acquirers’ stock prices before and after the announcement date. Our event day is based on the M&A announced date of Swedish listed acquirers. Moreover, our time parameter definition is explained below: 1) Announcement date: Our announcement date is extracted from the information reported by

Zephyr. If the announcement date is the day when the stock market is declared closed, we define the announcement date to be the first business day after the closing declaration.

2) Relative days: 0 for M&A event announcement day, with -t as t days before the announcement date, + t is expressed as t days after the announcement date.

3) Estimation Window: (t-240, t-31), our estimation period is 210 days. 4) Event Window: In addition to the (1, +1) as the main event window, we also choose (-2, +2),

(0, +2) , (-10,10) to support our main event window to observe the immediate before-event and post-event impact by the event relative to the available information, (-10,10) here is our longer short-term period event window for us to investigate the longer influence by the event. We refer our event windows based on the previous literature (Konchitchki, Y and Oĺeary, D.E, 2011)

T=(-240) T=(-30) T-1 T=0 T+1

FIGURE 2 : TIMELINE OF AN EVENT STUDY DESCRIBING THE ESTIMATION AND EVENT WINDOWS Obtaining expected return:

Expected return of individual stock price could be obtained by substituting and from the

estimation window, and are the estimation of the regression coefficients. Furthermore, we

use Nasdaq OMX Stockholm as the main market index for Sweden. , stem from ordinary least squares regression under our estimation window period (-240,-31), that is from day -240 to day -30 relative to event zero (0) day. We eliminate 30-day time interval (-30,-1) to avoid involving information of the event that might affect security returns.

,itmtiiit RR εβα ++=

α̂ β̂

α̂ β̂

α̂ β̂

Estimation Window

Event Window

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Obtaining abnormal returns:

ARit is the abnormal return for individual firm i on day t that equals to the difference between the actual return on day t and the expected return on day t. However, if we only apply actual return to our study, neither it can seize the impact of the event nor market movements can illustrate it. Deriving cumulative abnormal returns: Cumulative abnormal returns (CAR) are conducted by summing all the abnormal returns across our four event windows (t-1, t+1), (t-2, t+2), (t0, t+2), (t-10, t10). The CAR is an equally weighted abnormal return for the individual firms’ stocks in each day with respect to the announcements.

CARi(t1,t2)=   AR!!!! it

Deriving Average cumulative abnormal returns: Average cumulative abnormal returns is conducted by summing all the average abnormal returns:

ACAR= AARt!!!!!

Significance Test A t-test is performed for testing, if the cumulative abnormal returns have statistical significance. Practically, we do not know σεt2 , thus we calculate the variance of each company´s abnormal return to roughly estimated the variance of the average cumulative abnormal returns.

VAR(ACAR (t1, t2)) = !

!!𝜎!

!!! i2

t1,t2

t=   !"!#(!",!")√!"#(!"!#(!",!"))

t-test is also applied to test differences between two various groups I & II

t = !"!# !",!" !!!"!#(!",!")!!!"#(!"!# !",!" !!!"#(!"!#(!",!"))!!

3.2.1 Deal Specific characteristics A large numbers of researchers do the investigations if there are some particular factors that may affect the shareholders’ value and market reaction upon the M&A announcement, such as the firm size, and the relative size of the deal value to the market capitalization. Previous literatures record that various deal factors would influence the value creation of shareholders

)ˆ( ititit RERAR −=

mt

i i it

R R E β α ˆ ˆ ) ˆ ( + =

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(Markides & Ittner, 1994; Kiymaz & Mukherjee, 2000). However, different researches focus on different variables. Here, we choose payment method, deal type (technological & non-technological), relative size, and market capitalization as our control variables.

Moreover, table 1 shows that the sample compounds of the 502 M&A transactions derived from publicly listed Swedish companies during 2005-2105. We divide the subsections by acquisitions type and payment methods. The M&A type variable that is labelled as “Tech” displays the number of M&A of the targets that are conducted within primary 3-digit high-tech industry code (Kile & Phillips, 2009) or the targets have at least one patent being registered prior to the announcement. Furthermore, the variable type of ”non-tech” shows the number of deals that dissatisfied the above-mentioned categories.

Our sample of Swedish M&A consists of 62% that belongs to non-technological motivated deal, and 38% of the sample belongs to technological motivated deal. Moreover, we classify our payment methods into”All Cash” and ”All Stock”. The former stands for only cash financed deals and cash-deferred payment or earn-out, while the later is defined by only stock offerings and also the combination of stock and other payment methods where stock is a part of financing. Our classification of “All Stock” deals is due to a few data generated as pure stock financed deals from Zephyr. Two variables classification provides the permission to apply dummy variables later in our regression part. All stock financed deals account for 55% of the acquisitions in comparison to all cash financed that is 45% of deals. Also, both tech and non-tech subsamples tend to have more stock-financed transactions than cash-financed. ”Deal Value” and ”Market Capitalization” are reported by Zephyr in Millions US dollar, while ”Relative Size” is deal value divided by market capitalization on the announcement day.

Table 1. Deal Specific Characteristics

Number Percentage

Tech/ Non-Tech Tech 192 38 %

Non-Tech 308 62 %

Payment Method All Cash 224 45 %

All Stock 276 55 %

Tech & Payment Method All Cash 76 40 %

All Stock 116 60 %

Non-Tech & Payment Method All Cash 147 48 %

All Stock 161 52 %

Deal Value Less Than 5m 207 41 %

5 to 10m 52 10 %

10 to 50 m 115 23 %

50 to 100 m 39 8 %

More Than 100 m 87 17 %

Market Capitalization Less than 100m 107 21 %

100 to 500m 117 23 %

500 to 1000m 56 11 %

1000 to 5000m 84 17 %

More than 5000m 136 27 %

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Relative Size Less than 0.5% 198 40 %

0.5% to 5 % 137 27 %

5 % to 50 % 88 18 %

50 % to 75 % 11 2 %

More than 75 % 66 13 %

3.3 Regressions Josev, Chan & Faff (2004) identify regression analysis to approve the joint relationship between abnormal returns and explanatory variables on corporate financial event impacts. For our further research, we apply multivariate regression analysis to study if the payment method influences the acquiring firms’ short-term performance in Swedish M&A. The following ordinary least squares (OLS) regression model is used: (1) CAR (-1, +1) = βo + β1*all cash + β2*tech + β3*Relative Size + β4* Market Cap+Ԑ Where: Dependent Variable: CAR (-1, +1) = 3 days cumulative abnormal returns over the event window (-1, +1) or CAR (-10, +10) = 21 days cumulative abnormal returns over the event window (-10, +10) Independent Variable: All cash = dummy variable equals to 1 if the transaction is financed with pure cash or cash-deferred payment or earn-out, otherwise 0. Thus, the impact of payment method on CAR will be measured by β1. Control variables: Tech: dummy variable equals to 1 if targets are conducted within primary 3-digit high-tech industry code (Kile and Phillips, 2009) or the targets have at least one patent being registered prior to the announcement, otherwise 0. In this way, the effect on CAR by deals type will be captured by β2. Relative size: Ratio of deal value acquired from Zephyr to the market capitalisation value of acquiring firm at announcement. Market Cap: Acquirer’s market value reported from Zephyr, it is converted into natural logarithmic form in order to normalize the data. The above regression model corresponds to our hypothesis II: H0: β1=0 cash-financed deals generate negative or zero cumulative abnormal returns in Swedish M&A H1: β1≠ 0 cash-financed deals generate positive cumulative abnormal returns in Swedish M&A In the following model (2), an interaction variable “tech*all stock” is included to check whether the shares-financed payment would generate higher returns than cash-payment method for technological deals. Therefore, β3 interprets the impact on cumulative abnormal return based on the deal type and the means of financing method by bidders.

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(2) CAR (-1, +1) = βo + β1*all stock + β2*tech + β3*tech*all stock + β4*Relative Size + β5*Market Cap + Ԑ Thus, the regression echoed with statement from hypothesis IV:

H0: β3=0 stock financed deals generate negative or non-cumulative abnormal returns for technological M&A H1: β3≠ 0 stock financed deals generate positive cumulative abnormal returns for technological M&A

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4 Empirical Results and Discussions

4.1 Bidders’ value creation: short-run market reaction

In this chapter we write univariate analyses for the short-term value creation of bidders in Sweden. We compare and analyse various average CAR based on different characteristics of mergers and acquisitions that we focus on in this paper. Deal characteristics that we inspect under this chapter are firstly, methods of payment (cash or stock & mixed payment) for the whole M&A events. Secondly, type of acquisitions (technological or non-technological) for the eligible M&A events. Thirdly, choice of payment (cash or stock & mixed payment) for our technological M&A samples. Before we analyse different CAR of our theme characteristics, we start with the effect of announcement on short-term value creation for the acquirers.

4.1.1 Bidders’ market reaction to acquisition announcement Table 2 shows the summary of our sample average CAR across three different windows. The result of our empirical evidence shows that cumulative abnormal return for most of our event windows (t-1, t+1), (t-2, t+2), (t0, t+2) are significant and positive. It confirms our hypothesis 1 “Announcements of mergers and acquisitions are expected to increase bidders’ abnormal return at and around announcement”. From figure 3 it can be seen that there is a small but statistically significant abnormal return at the announcement day. The result is consistent with the previous findings that confirm the abnormal returns of shareholders’ acquirers are insignificantly different from zero. The recent research using Canadian sample by Dutta, Saadi & Zhu shows a small positive cumulative abnormal return at and around the announcement day. Moreover, studies using bigger market, such as, European market by Martynova & Rennebog (2006) and US market by Moeller & Schlingemann (2005) present small positive and statistically significant abnormal returns for the bidders’ acquirers. Martynova & Rennebog (2006) suggest that a smaller increase in bidders’ abnormal return is expected in comparison to target’s abnormal return. However, our finding opposes several researches studying bigger market such as US market by Mulherin & Boone (2000), Franks et al. (1991) and Healey et al. (1992) that confirm small negative abnormal returns for bidders. The first possible reason for the conflicting result between our Swedish samples’ small positive abnormal returns and US samples’ negative abnormal returns is the high concentration of ownership in Swedish market. A study by Baumik & Selarka (2012) proves a positive relationship between a large concentration of ownership and M&A performance. Firms with a high ownership concentration have higher controls over managers’ decisions, thus it mitigates the agency problem in acquisitions and managers will likely to participate in value enhancing acquisitions. Average Cumulative Abnormal Return for all of mergers and acquisitions (n=500). T-test is performed for these three different windows. Test significance at 10%=*, 5%=**, 1%=*** Table 2. Event Window (-1,+1) (-2,+2) (0,+2) 1. Announcement (n=500) Average CAR 0.03710*** 0.03594*** 0.0281*** T-Stat 9.67051 10.64599 8.4107

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Moreover, figure 3 shows that the market is efficient, as the announcement effect is incorporated into the stock prices of the acquirers rapidly. It can be captured from the difference between abnormal returns on t-1 and t0. Before the announcement, the abnormal return is close to zero though on t-1 day, the abnormal return has been higher than the average of CAR on other days’ prior and after announcements. Moreover, abnormal return on t0 is inflated quickly due the reaction to acquisitions announcement. However, figure 3 shows that the abnormal returns rapidly decrease after the announcement day. Figure 3. The average cumulative abnormal return of the whole samples from t-10 to t+10 trading days. The event’ announcement day is at t0

4.1.2 Payment method and bidders’ performance From table 3, we report cumulative abnormal return of acquisitions based on the choice of payment method. The result of cumulative abnormal returns across three event windows for cash and stock payment presents statistically significant and positive cumulative abnormal returns. Our samples show that involvement of shares payment in deals generate an approximately 2.4% higher cumulative abnormal return for acquirers than the involvement of cash payment in deals. Due to the result we reject our Hypothesis 2 “Mergers and Acquisitions financed in cash by bidders are more preferable than acquisitions financed in shares by bidders”. This result also contradicts the previous theory and various empirical evidences that support the outperformance of cash payment over stock payment in acquisitions. However, empirical researches regarding hubris theory show supports for the involvement of stock payment, as it is negatively associated with high premium. On the other hand, cash payment is positively associated with high premium that may prevent firms to gain from synergetic value. Hubris theory explains managerial overconfidence in valuation of targets, and it assumes that the manager is irrational. According to Roll (1986), when hubris theory exists, acquirers may not be able to gain synergetic value from acquisitions, thus, it explains acquirers’ loss in term of abnormal return. Other study that confirms a positive relationship between shares payment and abnormal returns is postulated by Chang (1998) in a study of private targets’ acquisitions. The

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acquisitions of private target create a large blockholder that is able to better monitor the combined companies’ managerial decisions. Moreover, as the variance of returns in stock deals from our Swedish sample is higher than cash payment acquisitions; this explains the higher preference of shares payment in Nordic deals. Most importantly, it makes clear that the higher usage of stock payment in our Swedish sample and Sweden in general. We will elaborate the reasons behind the preference of shares payment more later on under the chapter of analysis and discussion of deals specific characteristics. Average Cumulative Abnormal Return for payment method. T-test is performed for these three different windows. Test significance at 10%=*, 5%=**, 1%=*** Table 3. Event Window (-1, +1) (-2, +2) (0, +2) 1. Cash (n=224) Average CAR 0.02380*** 0.02383*** 0.02560*** T-Stat 9.26629 9.99547 10.02339 2. Shares & Mix (n=276) Average CAR 0.04789*** 0.04577*** 0.03032*** T-Stat 7.22347 7.88891 5.30958 3. Difference

Mean difference (2-1) 0.02409*** 0.02194*** 0.00472* T-Stat 5.93126 6.41944 1.49605

4.1.3 Technological M&A and bidders’ performance According to the market model of event study, we calculate the average abnormal returns (AR) and cumulative abnormal returns (CAR) based on the samples classified by merger type: technological M&A (192 deals) and Non-technological M&A (308 deals). As Table 4 shows the acquirers’ means cumulative abnormal returns (ACAR) over three event windows. Nevertheless, Mean difference of technological and non-technological M&A is crucial to investigate the significance that is not influenced by other deal characteristics. Generally, the investigated cumulative abnormal returns are positive. It indicates that shareholders of acquiring firm normally gain around the announcement. Furthermore, non-technological acquisitions generate higher cumulative abnormal returns than technological one. Non-technological deals have stronger market reaction with higher positive returns. The theoretical background behind it is the higher information asymmetry that high-tech acquisitions hold due to the valuation uncertainty of the high-tech assets. According to Canace & Mann (2013), it is hard to value the sustainable growth opportunities from the intangible assets in high-tech acquisitions. For technological M&A deals, the bidders obtain a significant cumulative abnormal return of around 3.1% at (t-1,+1) event window. Furthermore, for non-technological M&A deals, the mean cumulated abnormal returns for the acquiring firm is around 4.0% at (t-1, +1). However, the economic magnitude differences between the two subsamples are small and approximately range between 0.5% and 1.4%, which are statistically significant. Therefore, our empirical evidence opposes hypothesis III “Abnormal returns of bidders in non-technological acquisitions at and around announcement are less than those of bidders in technological acquisitions”. However, figure 4 where we compare the development of daily abnormal returns for technological and non-technological M&A ranging from t-3 to t+3 day shows interesting facts. Acquirers of non-technological M&A have lower abnormal returns than non-technological M&A on t-3 day, yet the development of the abnormal returns quickly change on t-2 for both technological M&A and non-technological M&A. Starting on t-2, non-technological M&A has higher abnormal returns than technological M&A. Moreover, the trend persists until t+3 that

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the non-technological M&A outperforms the technological M&A in term of abnormal returns. We believe that the rumor of acquisitions’ announcements has already commenced and influenced the abnormal returns starting on t-2 day. Our empirical evidence is consistent with the most recent technological M&A research by Sears & Hoetkers (2014) using US samples that confirms a negative association between technological M&A and bidders’ abnormal returns. Furthermore, Benou & Madura (2005) find positive but statistically insignificant abnormal returns on the announcement day based on US samples. However, the finding shows negative and statistically significant returns over the post-event window. The study elaborates that the acquisitions of public targets generate a negative cumulative abnormal returns, while the acquisitions of privately held targets yield positive abnormal return and favorable impacts. Most previous studies though are mainly focused on US market. It is very possible that the Swedish market differs from the US market in term of ownership concentration, and control of firms that may explain the variation of returns between US and Swedish market. Average Cumulative Abnormal Return for the deal type. T-test is performed for these three different windows. Test significance at 10%=*, 5%=**, 1%=*** Table 4. Event Window (-1, +1) (-2, +2) (0, +2) 1. Technological M&A (n=192) Average CAR 0.03072*** 0.02571*** 0.02382*** T-Stat 4.55390 4.63072 4.00299 2. Non-technological M&A (n=308) Average CAR 0.03950*** 0.04009*** 0.02951*** T-Stat 8.62909 9.45140 7.39848 3. Difference Mean difference (2-1) 0.00878*** 0.01438*** 0.00569*** T-Stat -4.05195 -10.97070 -2.90280 Figure 4. The average cumulative abnormal return for technological and non-technological deals from t-10 to t+10 trading days. The event’s announcement day is at t0

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tech non-tech

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4.1.4 Payment methods in technological M&A Table 5 displays the impact of the payment method on technological M&A based on three short-term period event windows. When we look at the event window (t-1, +1), generally, the cumulative abnormal returns are positive and also statistically significant in the range of 1.8% to 3.8% regardless of the all cash and all stock payment method. However, technological deals by stock-financed generate 1.9% higher cumulative returns than cash-financed. The result is consistent with our hypothesis IV “Technological acquisitions financed in shares by bidders are more preferable than technological acquisitions financed in cash by bidders” and also in accordance with the findings by Kohers & Kohers (2000); Cannace & Man (2013), that is, in technological acquisitions, stock financed deals would generate significant and positive returns. There are several possible explanatory reasons behind our result. Due to the high uncertainty in valuations of technological targets’ intangible assets and sustainable growth, one reason could be that the acquiring firm estimates the overvaluation of high-tech targets’ assets. Thus, based on the information asymmetry theory in this situation, stock payment will be chosen in the first place. This explains the first reason behind the preference of share payments in technological M&A. Moreover, Chartterjee & Kuenzi (2001) analyze the British M&A statistical data. Significantly positive abnormal returns upon the announcement are shown when the acquisitions are paid by stock, as the acquirers could not exactly capture the value of the target company. Since both parties face the risk of high bidding price as a result of asymmetric information, the acquirer could transfer risk through the use of stock payment, which also explains the reason for the increase of M&A by means of the exchange of shares. Another reason we prefer to see is the bidder’s returns for acquiring public and privately targets. Chang (1998) finds that stock offers earn a positive return of 2.64% for the acquirers of privately held firms. However, Travlos (1987) holds the opposite conclusion that stock-financed generates negative abnormal returns. In Swedish market, the typical structure is a dual shares system (Henrekson & Jakonson, 2011), which has an effect on the Swedish enterprise control market. Most of families and investment firms in Sweden are privately unlisted companies. Moreover, they have maintained control of listed firms in Sweden regardless of growing foreign and institutional proprietorship. The research also explains that privately held firms in Sweden have higher ownership concentrations than public firms. As a Swedish market consists of a high proportion of private firms, this also explains the preferences of shares payment in technological M&A in Sweden. Furthermore, because of the growing tech scenes in Sweden, many high-tech companies in Sweden have their exit strategies. This leads to a bias on cash payment acquisitions, as they are not interested in being under the acquirers’ operations and supervisions. Average Cumulative Abnormal Return for the payment method of technological M&A. T-test is performed for these three different windows. Test significance at 10%=*, 5%=**, 1%=*** Table 5. Event Window (-1,+1) (-2,+2) (0,+2) 1. Technological all cash (n=76) Average CAR 0.01899*** 0.01993*** 0.01962*** T-Stat 5.24390 6.27114 6.97992 2. Technological all shares (n=116) Average CAR 0.03840*** 0.02950*** 0.02657*** T-Stat 3.52012 3.29533 2.74639 3. Difference Mean difference (2-1) 0.01942*** 0.00956** 0.00695 T-Stat 2.66390 1.65663 1.01303

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4.2 Multivariate Analyses and Discussions We perform regression analyses in order to complement the univariate analyses under the previous chapter and explain deal specific characteristics variables that are not shown in the previous t statistic test. Moreover, the result from the OLS regression is shown in table 7. We choose the event window of (t-1, t+1,) as our main window, since the previous researchers find that this particular event window is able to significantly capture the short run momentum of firms’ shares price due to acquisitions. Furthermore, we include the longer event window of (t-10, t+10) as additional evidence and a comparison to (t-1, t+1,) event window.

Table 7. The table is derived from an OLR regression. CAR computes cumulative abnormal return around the announcement day for the bidders. All cash is a dummy variable for payment method. The value of the dummy variable is one if the payment method is cash, and zero otherwise. Tech is a dummy variable for the deal type. The value of the dummy variable is one if the payment method is technological M&A, and zero otherwise. Market cap is the natural logarithm value for market capitalisation of bidders. Relative size measures the ratio of deal values to bidders’ market capitalisation. We perform test significance at 10%=*, 5%=**, 1%=***. Dependent variables: CAR (-1, +1) CAR (-10, +10) β t-value β t-value Intercept 0.06382*** 3.921274 -0.011481 -0.427426 All Cash -0.022543** -2.124240 0.004183 0.238838 Tech -0.011342 -1.045862 0.013105 0.732214 Market cap -0.00213 -1.073482 0.003560 1.085958 Relative Size 0.001708*** 2.568004 N 491 491 F 3.719133 1.105588 R-squared 0.029071 0.009017 Adjusted R-square 0.021715 0.000861

The intercept of regression 1 on our main window of interest (t-1, t+1,) is positive and significant at 1% level. As the intercept is positive, it shows that the announcements of mergers and acquisitions generate 6,38% cumulative abnormal returns given other coefficients are equal to zero. Moreover, this evidence complements and supports our univariate t test for our first hypothesis that the announcements of mergers and acquisitions increase bidders’ abnormal returns. Thus, we accept our first hypothesis.

From regression 1, we can see that the coefficient of “all cash” variable is negative and statistically significant at 5% level. Thus, we can accept the null hypothesis that “cash payment has none or negative abnormal returns” in Swedish mergers and acquisitions. This hypothesis is compatible with our second hypothesis that has been discussed under the previous chapter. Thus, we reject the hypothesis regarding the preference of cash payment over shares payment in Swedish M&A.

The dummy “tech” variable from table 7 represents the technological M&A samples in our research. It has a negative coefficient, but it is not statistically significant. In Swedish market, it appears that the abnormal returns will decrease when the acquisitions are the technological ones. However, we cannot conclude that technological M&A is negatively associated with cumulative abnormal return. The “tech” variable though correlates with our hypothesis IV in the previous chapter. However, our t-test that controls solely payment method under previous chapter concludes that abnormal returns of bidders in technological M&A are less than those in non-technological M&A.

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Two other variables that we use as control variables are “market cap” and “relative size”. Table 7 shows a negative coefficient for the “market cap” variable. However, the test significant for this variable is statistically insignificant. Hence, there seems to be a tendency for larger acquirers to perform worse than smaller ones in Swedish market. Moreover, the “relative size” variable is positive and statistically significant at 1% level. This result is consistent with the previous research by Asquith et al. (1983) that presents positive relationship between relative size of target and bidders’ return. This also means that the higher the deal size of targets will lead to higher acquirers’ abnormal returns in Swedish M&A.

Furthermore, given the longer time frame (t-10, t+10) and the data collected for the event window (t-10, t+10), the regression model is not significant, thus we cannot conclude that there is relationship between M&A announcements’ characteristics studied in this paper and bidders’ performance for the event window of (t-10, t+10). In comparison with the previous study by Travlos (1987) regarding M&A choice of payment that explores the same event window from t-10 to t+10. The research shows statistically insignificant cumulative abnormal returns for most of the days within the time frame, yet the abnormal returns for shorter daily event window at t-1 and t0 are significant. Furthermore, as we observe the movement of abnormal returns from figure 3 and figure 4 between t-10 and t+10, we can see that there are some fluctuations, however the daily CARs for most of days are very close to zero. The short run momentum is only visible within the shorter time frame from the announcement. This may appear that the abnormal returns’ movement for longer daily event window t days follows random walk. From table 3 CAR slowly increases from t-4 day and sharply increases between t-1 and t0. Based on the figure 3, we may assume that the announcement has affected and inflated the stock price on t-1 trading day. When we look at figure 3 and 4, it appears that the distribution of most of daily cumulative abnormal returns are close to zero and both figure 3 and 4 may support our regression models’ results for the event window of (t-10, t+10) which shows no significant relationships between M&A announcements’ characteristics and CAR.

From table 8, we have an interaction term variable of “tech*all shares”. This helps us to apprehend the effect of shares payment involvement in technological M&A on abnormal returns. From the regression 2 we can see that “tech*all shares” variable has a small negative coefficient and it is very close to zero. However, the coefficient “tech*all shares” is not statistically significant. Hence, we cannot accept our null hypothesis, and we conclude that the shares payment in technological M&A does not generate zero or negative abnormal return in technological M&A.

Table 8. The table is derived from an OLR regression. CAR computes cumulative abnormal return around the announcement day for the bidders. All shares is a dummy variable for payment method. The value of the dummy variable is one if the payment method is shares, and zero otherwise. Tech is a dummy variable for the deal type. The value of the dummy “tech” variable is one if the payment method is technological M&A, and zero otherwise. Market cap is the natural logarithm value for market capitalisation of bidders. Relative size measures the ratio of deal values to bidders’ market capitalisation. “Tech*All Shares* is the interaction term to capture the involvement of shares payment in technological M&A. We perform test significance at 10%=*, 5%=**, 1%=***. Dependent variables: CAR (-1, +1) CAR (-10, +10) β t-value β t-value Intercept 0.041059*** 2.435346 -0.004558 -0.163826 All Shares 0.022895** 1.707446 -0.008621 -0.389592 Tech -0.010798 -1.045862 0.006237 0.226616 Market cap -0.002127 -1.068564 0.003502 1.065897 Relative Size 0.001707*** 2.561898 -0.001466 -1.333947 Tech*All Shares -0.000945 -0.042957 0.011935 0.328664 N 491 491 F 2.969565 0.904451 R-squared 0.029705 0.009238 Adjusted R-square 0.029705 -0.000976

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The preferences of stock payment in both the whole Swedish sample and Swedish technological M&A have not been explored in the previous findings. Moreover, the reasons behind them are difficult to settle. As it has been mentioned earlier under previous chapter, the empirical research by Chang (1998) confirms that shares offer for privately held targets generate positive abnormal returns. Other preferences of stock payment in previous studies are motivated by large managerial ownerships (Gosh & Ruland, 1998). The larger the managerial ownership the more likely it is for targets’ to accept shares payment. According to Gosh & Ruland (1998), targets’ managers are more likely to accept shares payment, as it is highly associated with job retention of targets’ managers. These reasons may explain the preferences of stock payment in Swedish market. Nevertheless, we do not make an analysis of Swedish targets’ ownership structure, it is very likely that Swedish samples consist of a huge amount of private firms as targets in Swedish M&A. Moreover, the previous research by Henrekson & Jakonson (2011) confirms a high proportion of Swedish private firms.

Based on our findings, Swedish acquirers are in favour of stock payment in technological M&A. A research of US samples by Canace & Mann (2013) supported our finding, as they discover that there is a negative association between cash payment and abnormal returns. Thus, their research confirms stock payments are more preferable than cash payments in technological M&A. The reason behind the preference of shares payments in Swedish technological M&A is likely to be similar with the reasons behind the preferences of shares payment in our whole sample for Swedish M&A. Other reason is explained in the previous chapter that is acquirers’ estimation of targets’ assets’ overvaluation, thus acquirers choose stock payment. Moreover, a high-tech M&A research that is based on US sample is also in line with our finding. It confirms that acquirers in US market are more in favour of shares payments than cash payments.

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5 Conclusion

In this paper, we conduct an event study in order to measure the effect of announcement on short-term value creation of bidders. Moreover, it is represented by bidders’ abnormal returns at and around announcement. We also explore the variation of abnormal returns by examining the characteristics of M&A especially payment method. The deal type of acquisitions that is technological M&A and non-technological M&A is also explored in this paper. We examine how the technological-motivated M&A explains the variation of acquirers’ abnormal returns. The sample of our paper consists of Swedish market over ten years’ period between 2005 and 2015. We find 500 deals that consist of 308 deals that belongs to non-technological M&A and 192 deals that are classified as technological M&A. Based on our empirical evidence, we find that the announcement of mergers and acquisitions generate statistically significant and positive abnormal returns at 1% level across three different event windows of interest. We believe that the reason behind it is due to the high concentration of ownership in Swedish firms. Hence, it will be more likely for the companies to engage in value increasing acquisitions. Moreover, we discover that shares payments are more preferable than cash payments in Swedish acquisitions. Shares payments generate 2.4% higher cumulative abnormal returns than cash payments on our main event window (t-1, t+1). As we control deal characteristics on OLS regression, we find a negative association between cash payment and cumulative abnormal returns. However, this result opposes the omnipresent preference of cash payments over shares payments in acquisitions. Based on previous literatures, the reasons behind this are due to the ownership structure and larger managerial ownership of targets. When companies acquire private targets, shares payment will generate higher abnormal returns than cash payments. We believe that these reasons are possibly applicable for the case of Swedish firms and market, as Sweden consists of relatively high amount of private companies.

Our empirical evidence regarding technological acquisitions confirms that the technological M&A in Sweden yields less abnormal returns than non-technological M&A. On OLS regressions, we find a negative coefficient for technological M&A, though it is statistically not significant. This finding is in line with a research by Sears & Hoetkers (2014) that documents a negative association between technological M&A and abnormal returns. However, our finding opposes other previous research that documents positive abnormal returns at and around announcement. Based on the recent previous research by Canace & Mann (2013), the lack of success of technological M&A is due to the markets’ overvaluation of intangible assets and growth opportunities of technological companies. Moreover, according to our finding regarding payment methods in technological M&A, it shows that shares payments are more preferable than cash payments. Though, the reason for Swedish market is difficult to resolve, as we exclude the classification of targets’ ownership structure. The previous research confirms that shares payments are preferable when acquiring private targets. Moreover, we also believe that the exit strategy of many high-tech companies in Sweden is a possible reason for the higher involvement of shares payment. The previous research states that the cash payment biased in privately high-tech companies exist.

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